Prunus sibirica L. is a key ecological and economic tree species in northern China that is threatened by habitat degradation due to climate change and human activities. To address the gaps of incomplete historical dynamics and lack of conservation integration in existing studies, we integrated MaxEnt and Zonation v4.0 to predict its suitable habitat across five periods (LIG to 2090s) and three CMIP6 SSP scenarios, identifying key drivers and priority conservation zones. The model showed high prediction accuracy (mean AUC > 0.9). Results indicated that Human Footprint (HFP), Precipitation Seasonality (Bio15), Annual Mean Temperature (Bio1), Elevation (ELEV), and Mean Temperature of the Coldest Quarter (Bio11) were the key environmental factors (cumulative contribution 91.4%), with Bio1, Bio15, Temperature Seasonality (Bio4), and HFP confirmed as major drivers (AUC > 0.8) via jackknife test. Spatiotemporally, the species’ suitable habitat contracted from the Last Interglacial to the Last Glacial Maximum and expanded to the current total suitable area of 506,620.1 km2. Under future SSP scenarios, suitable habitats expanded continuously under SSP126 and SSP245 but showed a “first expansion then contraction” trend under SSP585, with a persistent northeastward migration of the habitat centroid. The vertical (altitudinal) distribution of P. sibirica showed a trend of moving to higher elevations under future warming scenarios, especially in the SSP585 scenario. High-priority conservation zones are concentrated in northern China with insufficient existing protection. It is emphasized that this study contributes to improving the adaptive capacity and genetic characterization of P. sibirica almond populations to future climate.
Chen et al. (Mon,) studied this question.